934 resultados para INTERPRETATION


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We present a novel general resource analysis for logic programs based on sized types. Sized types are representations that incorporate structural (shape) information and allow expressing both lower and upper bounds on the size of a set of terms and their subterms at any position and depth. They also allow relating the sizes of terms and subterms occurring at different argument positions in logic predicates. Using these sized types, the resource analysis can infer both lower and upper bounds on the resources used by all the procedures in a program as functions on input term (and subterm) sizes, overcoming limitations of existing resource analyses and enhancing their precision. Our new resource analysis has been developed within the abstract interpretation framework, as an extension of the sized types abstract domain, and has been integrated into the Ciao preprocessor, CiaoPP. The abstract domain operations are integrated with the setting up and solving of recurrence equations for inferring both size and resource usage functions. We show that the analysis is an improvement over the previous resource analysis present in CiaoPP and compares well in power to state of the art systems.

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CENTER FOR NATURE INTERPRETATION II, LANZAROTE (2012). Texto en inglés y español

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A black plane. The place is an extraordinary landscape, black due to the ash of this volcanic island, the distant horizon and sea in the background to the west. A natural ring of hills surrounds a flat area that reaches to the sea, with a saltwater lake in the center, where the white salt mines were formed in the past century.

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Ejemplos de cómo los macrorrestos ayudan a mejorar la interpretación del paisaje vegetal de la península Ibérica

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Resource analysis aims at inferring the cost of executing programs for any possible input, in terms of a given resource, such as the traditional execution steps, time ormemory, and, more recently energy consumption or user defined resources (e.g., number of bits sent over a socket, number of database accesses, number of calls to particular procedures, etc.). This is performed statically, i.e., without actually running the programs. Resource usage information is useful for a variety of optimization and verification applications, as well as for guiding software design. For example, programmers can use such information to choose different algorithmic solutions to a problem; program transformation systems can use cost information to choose between alternative transformations; parallelizing compilers can use cost estimates for granularity control, which tries to balance the overheads of task creation and manipulation against the benefits of parallelization. In this thesis we have significatively improved an existing prototype implementation for resource usage analysis based on abstract interpretation, addressing a number of relevant challenges and overcoming many limitations it presented. The goal of that prototype was to show the viability of casting the resource analysis as an abstract domain, and howit could overcome important limitations of the state-of-the-art resource usage analysis tools. For this purpose, it was implemented as an abstract domain in the abstract interpretation framework of the CiaoPP system, PLAI.We have improved both the design and implementation of the prototype, for eventually allowing an evolution of the tool to the industrial application level. The abstract operations of such tool heavily depend on the setting up and finding closed-form solutions of recurrence relations representing the resource usage behavior of program components and the whole program as well. While there exist many tools, such as Computer Algebra Systems (CAS) and libraries able to find closed-form solutions for some types of recurrences, none of them alone is able to handle all the types of recurrences arising during program analysis. In addition, there are some types of recurrences that cannot be solved by any existing tool. This clearly constitutes a bottleneck for this kind of resource usage analysis. Thus, one of the major challenges we have addressed in this thesis is the design and development of a novel modular framework for solving recurrence relations, able to combine and take advantage of the results of existing solvers. Additionally, we have developed and integrated into our novel solver a technique for finding upper-bound closed-form solutions of a special class of recurrence relations that arise during the analysis of programs with accumulating parameters. Finally, we have integrated the improved resource analysis into the CiaoPP general framework for resource usage verification, and specialized the framework for verifying energy consumption specifications of embedded imperative programs in a real application, showing the usefulness and practicality of the resulting tool.---ABSTRACT---El Análisis de recursos tiene como objetivo inferir el coste de la ejecución de programas para cualquier entrada posible, en términos de algún recurso determinado, como pasos de ejecución, tiempo o memoria, y, más recientemente, el consumo de energía o recursos definidos por el usuario (por ejemplo, número de bits enviados a través de un socket, el número de accesos a una base de datos, cantidad de llamadas a determinados procedimientos, etc.). Ello se realiza estáticamente, es decir, sin necesidad de ejecutar los programas. La información sobre el uso de recursos resulta muy útil para una gran variedad de aplicaciones de optimización y verificación de programas, así como para asistir en el diseño de los mismos. Por ejemplo, los programadores pueden utilizar dicha información para elegir diferentes soluciones algorítmicas a un problema; los sistemas de transformación de programas pueden utilizar la información de coste para elegir entre transformaciones alternativas; los compiladores paralelizantes pueden utilizar las estimaciones de coste para realizar control de granularidad, el cual trata de equilibrar el coste debido a la creación y gestión de tareas, con los beneficios de la paralelización. En esta tesis hemos mejorado de manera significativa la implementación de un prototipo existente para el análisis del uso de recursos basado en interpretación abstracta, abordando diversos desafíos relevantes y superando numerosas limitaciones que éste presentaba. El objetivo de dicho prototipo era mostrar la viabilidad de definir el análisis de recursos como un dominio abstracto, y cómo se podían superar las limitaciones de otras herramientas similares que constituyen el estado del arte. Para ello, se implementó como un dominio abstracto en el marco de interpretación abstracta presente en el sistema CiaoPP, PLAI. Hemos mejorado tanto el diseño como la implementación del mencionado prototipo para posibilitar su evolución hacia una herramienta utilizable en el ámbito industrial. Las operaciones abstractas de dicha herramienta dependen en gran medida de la generación, y posterior búsqueda de soluciones en forma cerrada, de relaciones recurrentes, las cuales modelizan el comportamiento, respecto al consumo de recursos, de los componentes del programa y del programa completo. Si bien existen actualmente muchas herramientas capaces de encontrar soluciones en forma cerrada para ciertos tipos de recurrencias, tales como Sistemas de Computación Algebraicos (CAS) y librerías de programación, ninguna de dichas herramientas es capaz de tratar, por sí sola, todos los tipos de recurrencias que surgen durante el análisis de recursos. Existen incluso recurrencias que no las puede resolver ninguna herramienta actual. Esto constituye claramente un cuello de botella para este tipo de análisis del uso de recursos. Por lo tanto, uno de los principales desafíos que hemos abordado en esta tesis es el diseño y desarrollo de un novedoso marco modular para la resolución de relaciones recurrentes, combinando y aprovechando los resultados de resolutores existentes. Además de ello, hemos desarrollado e integrado en nuestro nuevo resolutor una técnica para la obtención de cotas superiores en forma cerrada de una clase característica de relaciones recurrentes que surgen durante el análisis de programas lógicos con parámetros de acumulación. Finalmente, hemos integrado el nuevo análisis de recursos con el marco general para verificación de recursos de CiaoPP, y hemos instanciado dicho marco para la verificación de especificaciones sobre el consumo de energía de programas imperativas embarcados, mostrando la viabilidad y utilidad de la herramienta resultante en una aplicación real.

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Peer reviewed

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Euan Macrae was funded by a NERC Open CASE PhD award (NE/F013728/1) with Midland Valley Exploration Ltd. as the industry partner. We thank the 763 geoscientists for their participation, and in particular, the reference experts who gave their time freely to the project. Marian Scott (University of Glasgow, UK) is thanked for assisting with the statistical analysis. Four reviewers are thanked for their constructive comments which improved the manuscript.

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This paper decomposes the conventional measure of selection bias in observational studies into three components. The first two components are due to differences in the distributions of characteristics between participant and nonparticipant (comparison) group members: the first arises from differences in the supports, and the second from differences in densities over the region of common support. The third component arises from selection bias precisely defined. Using data from a recent social experiment, we find that the component due to selection bias, precisely defined, is smaller than the first two components. However, selection bias still represents a substantial fraction of the experimental impact estimate. The empirical performance of matching methods of program evaluation is also examined. We find that matching based on the propensity score eliminates some but not all of the measured selection bias, with the remaining bias still a substantial fraction of the estimated impact. We find that the support of the distribution of propensity scores for the comparison group is typically only a small portion of the support for the participant group. For values outside the common support, it is impossible to reliably estimate the effect of program participation using matching methods. If the impact of participation depends on the propensity score, as we find in our data, the failure of the common support condition severely limits matching compared with random assignment as an evaluation estimator.

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Objective To review critically the statistical methods used for health economic evaluations in randomised controlled trials where an estimate of cost is available for each patient in the study.

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We review the current status of our knowledge of cosmic velocity fields, on both small and large scales. A new statistic is described that characterizes the incoherent, thermal component of the velocity field on scales less than 2h−1 Mpc (h is H0/100 km·s−1·Mpc−1, where H0 is the Hubble constant and 1 Mpc = 3.09 × 1022 m) and smaller. The derived velocity is found to be quite stable across different catalogs and is of remarkably low amplitude, consistent with an effective Ω ∼ 0.15 on this scale. We advocate the use of this statistic as a standard diagnostic of the small-scale kinetic energy of the galaxy distribution. The analysis of large-scale flows probes the velocity field on scales of 10–60 h−1 Mpc and should be adequately described by linear perturbation theory. Recent work has focused on the comparison of gravity or density fields derived from whole-sky redshift surveys of galaxies [e.g., the Infrared Astronomical Satellite (IRAS)] with velocity fields derived from a variety of sources. All the algorithms that directly compare the gravity and velocity fields suggest low values of the density parameter, while the POTENT analysis, using the same data but comparing the derived IRAS galaxy density field with the Mark-III derived matter density field, leads to much higher estimates of the inferred density. Since the IRAS and Mark-III fields are not fully consistent with each other, the present discrepancies might result from the very different weighting applied to the data in the competing methods.

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The phenomenon of desensitization is universal, but its mechanism is still ill-understood and controversial. A recently published study [Lin, F. & Stevens, C. F. (1994) J. Neurosci, 14, 2153-2160] attempted to cast light on the mechanism of desensitization of N-methyl-D-aspartate (NMDA) receptors, in particular the vexed question of whether the channel must open before it can desensitize. During the desensitizing preexposure to agonist in those experiments, more desensitization was produced when channel openings were observed than when no openings were observed. The conclusion that "desensitization occurs more rapidly from the open state" unfortunately was based on a stochastic fallacy, and we present here a theoretical treatment and illustration showing that the observed behavior is predicted by a simple mechanism in which desensitization can occur only from a shut state.

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In 10-30% of hypertrophic cardiomyopathy kindreds, the disease is caused by > 29 missense mutations in the cardiac beta-myosin heavy chain (MYH7) gene. The amino acid sequence similarity between chicken skeletal muscle and human beta-cardiac myosin and the three-dimensional structure of the chicken skeletal muscle myosin head have provided the opportunity to examine the structural consequences of these naturally occurring mutations in human beta-cardiac myosin. This study demonstrates that the mutations are related to distinct structural and functional domains. Twenty-four are clustered around four specific locations in the myosin head that are (i) associated with the actin binding interface, (ii) around the nucleotide binding site, (iii) adjacent to the region that connects the two reactive cysteine residues, and (iv) in close proximity to the interface of the heavy chain with the essential light chain. The remaining five mutations are in the myosin rod. The locations of these mutations provide insight into the way they impair the functioning of this molecular motor and also into the mechanism of energy transduction.